论文库

原文摘要

An important challenge in homomorphic encryption (HE) is ensuring the integrity of the encrypted computations. Although verifiable computation can address this in theory, making it practical is far from trivial. [Cascudo et al. CRYPTO 2025] recently proposed a solution to this problem for the CKKS scheme. In particular, they propose new succinct arguments that efficiently prove arithmetic circuits and range checks over the ring $R_q = \mathbb{Z}_q[Y]/(Y^N+1)$, and combine them to prove computations on CKKS ciphertexts. Despite the important progress, their work faces scalability challenges: the size of the polynomial commitment proofs, a large $O(N)$ overhead in range proofs, and the lack of an explicit method for efficient -- sublinear in circuit size -- verification. In this paper we present new techniques that remove all these bottlenecks. First, we provide a more efficient arithmetization of CKKS computations. Second, we introduce BatchFold, a new polynomial commitment for $R_q$ that supports batched evaluations and achieves shorter proofs. Third, we design packing, a novel algebraic technique that eliminates the need to commit to massive polynomials and removes the $O(N)$ overhead in range proofs. Finally, we introduce SparsePack, an efficient protocol for proving the evaluations of sparse, circuit-dependent polynomials, leveraging both packing and batched evaluations. We evaluate the efficiency of our solution on a generic neural network architecture, achieving proofs several orders of magnitude smaller and faster than prior approaches.